Overview / Usage

The Recipe generator model I developed with Intel Extension for PyTorch is designed to simplify meal planning and enhance culinary creativity. By entering available ingredients, the model instantly provides personalized recipe suggestions, helping users make the most of what they have on hand. This solution addresses the common problem of deciding what to cook with limited ingredients, reducing food waste and adding variety to daily meals.

USAGE:

** ** Users have the option to generate recipes based on the ingredients they have on hand, making meal planning and preparation a breeze. The application's recipe generator analyzes user-provided ingredients and suggests delicious recipe options that utilize those items.

Methodology / Approach

The dataset used is obtained from Kaggle, it is imported to the notebook. Leveraging Intel Extension for PyTorch, this model benefits from the accelerated development and deployment processes facilitated by Intel Developer Cloud. By harnessing Intel's GPU capabilities, I have significantly reduced training times, ensuring efficient model optimization and experimentation. The process involves installing essential dependencies, fine-tuning GPT with a custom dataset, and configuring the model for recipe generation. This collaborative approach has led to remarkable speedups, enhancing the overall performance of my Recipe Generation model and streamlining the culinary creativity process.

Technologies Used

  This model represents a leap forward in culinary innovation, harnessing the power of GPT and Intel Extension for PyTorch. This groundbreaking model redefines culinary creativity by generating personalized recipes based on your ingredients. Leveraging the cutting-edge capabilities of GPT and Intel's technology, our model ensures seamless recipe generation.  

Intel oneAPI Integration:

1. Intel oneAPI Deep Neural Networks Library(one DNN)

i) Intel Extension for Pytorch

Repository

https://github.com/noornish/Recipe_generator